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Smn theorem

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On transforming a program by substituting constants for free variables

In computability theory the S m
theorem
, written also as "smn-theorem" or "s-m-n theorem" (also called the translation lemma, parameter theorem, and the parameterization theorem) is a basic result about programming languages (and, more generally, Gödel numberings of the computable functions) (Soare 1987, Rogers 1967). It was first proved by Stephen Cole Kleene (1943). The name S m
comes from the occurrence of an S with subscript n and superscript m in the original formulation of the theorem (see below).

In practical terms, the theorem says that for a given programming language and positive integers m and n, there exists a particular algorithm that accepts as input the source code of a program with m + n free variables, together with m values. This algorithm generates source code that effectively substitutes the values for the first m free variables, leaving the rest of the variables free.

The smn-theorem states that given a function of two arguments g ( x , y ) {\displaystyle g(x,y)} which is computable, there exists a total and computable function such that ϕ s ( x ) ( y ) = g ( x , y ) {\displaystyle \phi _{s}(x)(y)=g(x,y)} basically "fixing" the first argument of g {\displaystyle g} . It's like partially applying an argument to a function. This is generalized over m , n {\displaystyle m,n} tuples for x , y {\displaystyle x,y} . In other words, it addresses the idea of "parametrization" or "indexing" of computable functions. It's like creating a simplified version of a function that takes an additional parameter (index) to mimic the behavior of a more complex function.

The function s m n {\displaystyle s_{m}^{n}} is designed to mimic the behavior of ϕ ( x , y ) {\displaystyle \phi (x,y)} when given the appropriate parameters. Essentially, by selecting the right values for m {\displaystyle m} and n {\displaystyle n} , you can make s {\displaystyle s} behave like for a specific computation. Instead of dealing with the complexity of ϕ ( x , y ) {\displaystyle \phi (x,y)} , we can work with a simpler s m n {\displaystyle s_{m}^{n}} that captures the essence of the computation.

Details

The basic form of the theorem applies to functions of two arguments (Nies 2009, p. 6). Given a Gödel numbering φ {\displaystyle \varphi } of recursive functions, there is a primitive recursive function s of two arguments with the following property: for every Gödel number p of a partial computable function f with two arguments, the expressions φ s ( p , x ) ( y ) {\displaystyle \varphi _{s(p,x)}(y)} and f ( x , y ) {\displaystyle f(x,y)} are defined for the same combinations of natural numbers x and y, and their values are equal for any such combination. In other words, the following extensional equality of functions holds for every x:

φ s ( p , x ) λ y . φ p ( x , y ) . {\displaystyle \varphi _{s(p,x)}\simeq \lambda y.\varphi _{p}(x,y).}

More generally, for any m, n > 0, there exists a primitive recursive function S n m {\displaystyle S_{n}^{m}} of m + 1 arguments that behaves as follows: for every Gödel number p of a partial computable function with m + n arguments, and all values of x1, …, xm:

φ S n m ( p , x 1 , , x m ) λ y 1 , , y n . φ p ( x 1 , , x m , y 1 , , y n ) . {\displaystyle \varphi _{S_{n}^{m}(p,x_{1},\dots ,x_{m})}\simeq \lambda y_{1},\dots ,y_{n}.\varphi _{p}(x_{1},\dots ,x_{m},y_{1},\dots ,y_{n}).}

The function s described above can be taken to be S 1 1 {\displaystyle S_{1}^{1}} .

Formal statement

Given arities m and n, for every Turing Machine TM x {\displaystyle {\text{TM}}_{x}} of arity m + n {\displaystyle m+n} and for all possible values of inputs y 1 , , y m {\displaystyle y_{1},\dots ,y_{m}} , there exists a Turing machine TM k {\displaystyle {\text{TM}}_{k}} of arity n, such that

z 1 , , z n : TM x ( y 1 , , y m , z 1 , , z n ) = TM k ( z 1 , , z n ) . {\displaystyle \forall z_{1},\dots ,z_{n}:{\text{TM}}_{x}(y_{1},\dots ,y_{m},z_{1},\dots ,z_{n})={\text{TM}}_{k}(z_{1},\dots ,z_{n}).}

Furthermore, there is a Turing machine S that allows k to be calculated from x and y; it is denoted k = S n m ( x , y 1 , , y m ) {\displaystyle k=S_{n}^{m}(x,y_{1},\dots ,y_{m})} .

Informally, S finds the Turing Machine TM k {\displaystyle {\text{TM}}_{k}} that is the result of hardcoding the values of y into TM x {\displaystyle {\text{TM}}_{x}} . The result generalizes to any Turing-complete computing model.

This can also be extended to total computable functions as follows:

Given a total computable function s m , n : N m + 1 N {\displaystyle s_{m,n}:\mathbb {N} ^{m+1}\rightarrow \mathbb {N} } and m , n 1 {\displaystyle m,n\geq 1} such that x N m , y N n {\displaystyle \forall {\vec {x}}\in \mathbb {N} ^{m},\forall {\vec {y}}\in \mathbb {N} ^{n}} , e N {\displaystyle \forall e\in \mathbb {N} } :

ϕ e m + n ( x , y ) = ϕ s m , n ( e , x ) n ( y ) {\displaystyle \phi _{e}^{m+n}({\vec {x}},{\vec {y}})=\phi _{s_{m,n}{(e,{\vec {x}})}}^{n}({\vec {y}})}

There is also a simplified version of the same theorem (defined infact as "simplified smn-theorem", which basically uses a total computable function as index as follows:

Let f : N n + m N {\displaystyle f:\mathbb {N} ^{n+m}\rightarrow \mathbb {N} } be a computable function. There, there is a total computable function s : N m N {\displaystyle s:\mathbb {N} ^{m}\rightarrow \mathbb {N} } such that x N m {\displaystyle \forall x\in \mathbb {N} ^{m}} , y N n {\displaystyle {\vec {y}}\in \mathbb {N} ^{n}} :

f ( x , y ) = ϕ S ( x ) ( n ) ( y ) {\displaystyle f({\vec {x}},{\vec {y}})=\phi _{S({\vec {x}})}^{(n)}({\vec {y}})}

Example

The following Lisp code implements s11 for Lisp.

(defun s11 (f x)
  (let ((y (gensym)))
    (list 'lambda (list y) (list f x y))))

For example, (s11 '(lambda (x y) (+ x y)) 3) evaluates to (lambda (g42) ((lambda (x y) (+ x y)) 3 g42)).

See also

References

External links

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